Re: New Possibilities Using Trainable Digital Logic

On 29 Dec 2005 22:45:13 -0800, bsmithtech@xxxxxxxx wrote:

>Hello,
>
>I thought I would share this informaton with the group and start a new
>topic. I came across this information the other day regarding neural
>networks and the applications in electronic design. Take a look below.
>
>A long time goal of artificial intelligence (AI) is the development of
>methods that can learn from examples to recognize events and make
>decisions. For example, automatic recognition of speech is already in
>widespread use, although this technology is far from usable in ordinary
>conversations. Another example is the recognition of handwriting; here
>the technology is still primitive. The eventual wide-spread consumer
>use of decision making machines and robotics will depend on the
>development of powerful, inexpensive, trainable devices which will
>allow the evolution towards thinking machines with capabilities far in
>excess of today's speech processors and robots.
>
>NSC was founded to exploit a trainable high-speed technology called
>trainable digital logic (TDL) that is inexpensive to implement for
>recognition and decision making. TDL could form a basis for widespread
>use of broader AI technology.
>
>Consider a digital device that performs recognition and outputs a yes
>or a no when the input is a digital word. For example, the input might
>be numbers that are parameters characterizing an electrocardiogram
>(ECG) beat, and the device must decide if the beat is a dangerous
>arrhythmia.
>
>When a sequence of bits is input to a logic circuit, which then outputs
>a 1 or a 0, (e.g., answers yes or no), the circuit is called a
>switching function. All digitally implemented pattern recognizers (such
>as neural networks) that have a binary output are, in fact, switching
>functions.
>
>The word "trainable" means that examples of known categories (e.g.,
>both dangerous and normal ECG beats) and a training algorithm can be
>used to organize the device. The trained device will give the correct
>answer (classification) when presented with examples where the category
>is not known.
>
>A key to NSC's technology is the development of efficient training
>algorithms that can organize binary logic into complex switching
>functions by using only binary inputs from known categories. The number
>of categories need not be restricted to two; NSC has constructed logic
>for up to sixteen categories.
>
>I didn't want to put the full article here, so to read the full
>technology - you can find it here: http://www.neuralsyscorp.com

---
Sounds like a press release. You wouldn't happen to be SPAMming us,
would you?


--
John Fields
Professional Circuit Designer
.

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